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feat: add MiniMax as LLM provider
Add MiniMax as a first-class LLM provider to the Portkey AI Gateway, supporting MiniMax-M2.7 and MiniMax-M2.7-highspeed models via their OpenAI-compatible API at https://api.minimax.io/v1. - Add provider files (api.ts, chatComplete.ts, index.ts) with streaming support and response transforms - Register provider in globals, provider index, providers.json, and models.json - Use open-ai-base for chat completion params with temperature default of 1.0 - Exclude unsupported params: logit_bias, logprobs, top_logprobs - Add 22 unit tests covering config, transforms, and streaming - Add 3 integration tests with real API validation - Add test variables entry for MINIMAX_API_KEY Co-authored-by: PR Bot <pr-bot@minimaxi.com> Signed-off-by: kapelame <kapelame@users.noreply.github.com>
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‎src/data/models.json‎

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"id": "openai"
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},
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"name": "Text Embedding Ada 002"
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},
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{
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"id": "MiniMax-M2.7",
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"object": "model",
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"provider": {
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"id": "minimax"
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},
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"name": "MiniMax M2.7"
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},
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{
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"id": "MiniMax-M2.7-highspeed",
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"object": "model",
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"provider": {
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"id": "minimax"
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},
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"name": "MiniMax M2.7 Highspeed"
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}
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]
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}

‎src/data/providers.json‎

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"object": "provider",
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"description": "Dashscope provides intelligent analytics solutions designed to help businesses visualize and interpret complex data effectively. Their platform integrates advanced machine learning algorithms to generate real-time insights from diverse datasets, enabling organizations to make informed decisions quickly. Dashscope focuses on enhancing data accessibility and usability, empowering teams to leverage analytics for strategic planning and operational efficiency.",
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"base_url": "https://dashscope.aliyuncs.com/compatible-mode/v1"
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},
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{
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"id": "minimax",
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"name": "MiniMax",
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"object": "provider",
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"description": "MiniMax is a leading AI company that develops advanced large language models including MiniMax-M2.7 and MiniMax-M2.7-highspeed. Their models support 204,800 tokens context window and are accessible via an OpenAI-compatible API, enabling seamless integration for text generation, chat, and tool-calling applications.",
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"base_url": "https://api.minimax.io/v1"
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}
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]
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}

‎src/globals.ts‎

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@@ -113,6 +113,7 @@ export const ORACLE: string = 'oracle';
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export const IO_INTELLIGENCE: string = 'iointelligence';
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export const AIBADGR: string = 'aibadgr';
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export const OVHCLOUD: string = 'ovhcloud';
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export const MINIMAX: string = 'minimax';
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export const VALID_PROVIDERS = [
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ANTHROPIC,
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IO_INTELLIGENCE,
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AIBADGR,
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OVHCLOUD,
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MINIMAX,
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];
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export const CONTENT_TYPES = {

‎src/providers/index.ts‎

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@@ -74,6 +74,7 @@ import OracleConfig from './oracle';
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import IOIntelligenceConfig from './iointelligence';
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import AIBadgrConfig from './aibadgr';
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import OVHcloudConfig from './ovhcloud';
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import MiniMaxConfig from './minimax';
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const Providers: { [key: string]: ProviderConfigs } = {
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openai: OpenAIConfig,
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iointelligence: IOIntelligenceConfig,
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aibadgr: AIBadgrConfig,
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ovhcloud: OVHcloudConfig,
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minimax: MiniMaxConfig,
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};
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export default Providers;

‎src/providers/minimax/api.ts‎

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import { ProviderAPIConfig } from '../types';
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const MiniMaxAPIConfig: ProviderAPIConfig = {
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getBaseURL: () => 'https://api.minimax.io/v1',
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headers: ({ providerOptions }) => {
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return {
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Authorization: `Bearer ${providerOptions.apiKey}`,
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};
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},
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getEndpoint: ({ fn }) => {
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switch (fn) {
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case 'chatComplete':
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return '/chat/completions';
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default:
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return '';
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}
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},
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};
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export default MiniMaxAPIConfig;

‎src/providers/minimax/chatComplete.ts‎

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import { MINIMAX } from '../../globals';
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import { ChatCompletionResponse, ErrorResponse } from '../types';
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import {
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generateErrorResponse,
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generateInvalidProviderResponseError,
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} from '../utils';
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export interface MiniMaxChatCompleteResponse extends ChatCompletionResponse {}
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export interface MiniMaxErrorResponse extends ErrorResponse {}
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export interface MiniMaxStreamChunk {
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id: string;
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object: string;
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created: number;
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model: string;
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choices: {
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delta: {
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role?: string | null;
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content?: string;
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tool_calls?: object[];
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};
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index: number;
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finish_reason: string | null;
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}[];
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usage?: {
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prompt_tokens: number;
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completion_tokens: number;
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total_tokens: number;
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};
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}
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export const MiniMaxChatCompleteResponseTransform: (
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response: MiniMaxChatCompleteResponse | MiniMaxErrorResponse,
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responseStatus: number
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) => ChatCompletionResponse | ErrorResponse = (response, responseStatus) => {
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if ('error' in response && responseStatus !== 200) {
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return generateErrorResponse(
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{
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message: response.error.message,
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type: response.error.type,
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param: null,
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code: response.error.code?.toString() || null,
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},
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MINIMAX
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);
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}
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if ('choices' in response) {
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return {
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id: response.id,
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object: response.object,
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created: response.created,
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model: response.model,
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provider: MINIMAX,
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choices: response.choices.map((c) => ({
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index: c.index,
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message: c.message,
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logprobs: c.logprobs,
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finish_reason: c.finish_reason,
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})),
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usage: {
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prompt_tokens: response.usage?.prompt_tokens || 0,
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completion_tokens: response.usage?.completion_tokens || 0,
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total_tokens: response.usage?.total_tokens || 0,
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},
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};
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}
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return generateInvalidProviderResponseError(response, MINIMAX);
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};
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export const MiniMaxChatCompleteStreamChunkTransform: (
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response: string
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) => string = (responseChunk) => {
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let chunk = responseChunk.trim();
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chunk = chunk.replace(/^data: /, '');
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chunk = chunk.trim();
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if (chunk === '[DONE]') {
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return `data: ${chunk}\n\n`;
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}
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const parsedChunk: MiniMaxStreamChunk = JSON.parse(chunk);
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return (
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`data: ${JSON.stringify({
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id: parsedChunk.id,
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object: parsedChunk.object,
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created: parsedChunk.created,
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model: parsedChunk.model,
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provider: MINIMAX,
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choices:
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parsedChunk.choices && parsedChunk.choices.length > 0
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? [
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{
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index: parsedChunk.choices[0].index || 0,
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delta: {
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role: parsedChunk.choices[0].delta?.role || undefined,
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content: parsedChunk.choices[0].delta?.content || '',
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tool_calls:
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parsedChunk.choices[0].delta?.tool_calls || undefined,
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},
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finish_reason: parsedChunk.choices[0].finish_reason || null,
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},
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]
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: [],
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usage: parsedChunk.usage
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? {
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prompt_tokens: parsedChunk.usage.prompt_tokens || 0,
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completion_tokens: parsedChunk.usage.completion_tokens || 0,
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total_tokens: parsedChunk.usage.total_tokens || 0,
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}
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: undefined,
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})}` + '\n\n'
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);
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};

‎src/providers/minimax/index.ts‎

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import { MINIMAX } from '../../globals';
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import { chatCompleteParams, responseTransformers } from '../open-ai-base';
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import { ProviderConfigs } from '../types';
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import MiniMaxAPIConfig from './api';
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import { MiniMaxChatCompleteStreamChunkTransform } from './chatComplete';
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const MiniMaxConfig: ProviderConfigs = {
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chatComplete: chatCompleteParams(
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['logit_bias', 'logprobs', 'top_logprobs', 'parallel_tool_calls'],
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{ temperature: 1 },
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{
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response_format: {
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param: 'response_format',
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default: null,
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},
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}
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),
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api: MiniMaxAPIConfig,
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responseTransforms: {
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...responseTransformers(MINIMAX, {
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chatComplete: true,
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}),
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'stream-chatComplete': MiniMaxChatCompleteStreamChunkTransform,
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},
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};
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export default MiniMaxConfig;

‎src/tests/minimax.integration.test.ts‎

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/**
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* Integration tests for MiniMax provider.
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* These tests call the real MiniMax API and require MINIMAX_API_KEY env var.
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* Run with: npx jest src/tests/minimax.integration.test.ts
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*/
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const MINIMAX_API_KEY = process.env.MINIMAX_API_KEY;
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const BASE_URL = 'https://api.minimax.io/v1';
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const skipIfNoKey = MINIMAX_API_KEY ? describe : describe.skip;
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skipIfNoKey('MiniMax integration tests', () => {
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test('non-streaming chat completion with MiniMax-M2.7', async () => {
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const response = await fetch(`${BASE_URL}/chat/completions`, {
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method: 'POST',
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headers: {
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Authorization: `Bearer ${MINIMAX_API_KEY}`,
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({
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model: 'MiniMax-M2.7',
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messages: [
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{ role: 'system', content: 'You are a helpful assistant.' },
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{ role: 'user', content: 'Say hello in one word.' },
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],
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max_tokens: 30,
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temperature: 1.0,
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stream: false,
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}),
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});
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expect(response.status).toBe(200);
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const data = await response.json();
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expect(data).toHaveProperty('id');
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expect(data).toHaveProperty('model');
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expect(data).toHaveProperty('choices');
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expect(data.choices.length).toBeGreaterThan(0);
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expect(data.choices[0]).toHaveProperty('message');
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expect(data.choices[0].message).toHaveProperty('content');
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expect(data).toHaveProperty('usage');
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expect(data.usage).toHaveProperty('prompt_tokens');
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expect(data.usage).toHaveProperty('completion_tokens');
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expect(data.usage).toHaveProperty('total_tokens');
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});
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test('streaming chat completion with MiniMax-M2.7-highspeed', async () => {
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const response = await fetch(`${BASE_URL}/chat/completions`, {
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method: 'POST',
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headers: {
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Authorization: `Bearer ${MINIMAX_API_KEY}`,
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({
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model: 'MiniMax-M2.7-highspeed',
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messages: [{ role: 'user', content: 'Say hi' }],
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max_tokens: 20,
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temperature: 1.0,
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stream: true,
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}),
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});
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expect(response.status).toBe(200);
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const text = await response.text();
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const lines = text
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.split('\n')
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.filter((line: string) => line.startsWith('data: '));
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expect(lines.length).toBeGreaterThan(0);
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// Check that the last meaningful chunk or a data chunk has proper structure
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const firstLine = lines[0];
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const firstData = JSON.parse(firstLine.replace('data: ', ''));
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expect(firstData).toHaveProperty('id');
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expect(firstData).toHaveProperty('model');
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expect(firstData).toHaveProperty('choices');
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// Verify at least one chunk has finish_reason
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const hasFinishReason = lines.some((line: string) => {
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try {
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const parsed = JSON.parse(line.replace('data: ', ''));
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return parsed.choices?.[0]?.finish_reason !== null;
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} catch {
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return false;
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}
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});
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expect(hasFinishReason).toBe(true);
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});
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test('error handling with invalid API key', async () => {
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const response = await fetch(`${BASE_URL}/chat/completions`, {
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method: 'POST',
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headers: {
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Authorization: 'Bearer invalid-key',
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({
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model: 'MiniMax-M2.7',
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messages: [{ role: 'user', content: 'Hello' }],
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max_tokens: 10,
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}),
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});
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expect(response.status).not.toBe(200);
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});
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});

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